Characterizing Long Interval Cortical Inhibition over the Time-Frequency Domain
Bibliographic record
Abstract
OBJECTIVE: Long-interval cortical inhibition (LICI) can be recorded from motor and non-motor regions of the cortex through combined transcranial magnetic stimulation (TMS) with electroencephalography (EEG). This study aimed to evaluate additional dimensions of LICI characteristics over an extended time-frequency and spatial domain. This was done by introducing two alternative measures of LICI signal amplitude: the Discrete Fourier Transform (DFT) and the Hilbert transform (HT). Both approaches estimate signal amplitude not taking into account the phase. In both cases LICI was measured as the difference between the unconditioned and conditioned activity evoked by the test pulse. Finally, we evaluated whether the topographical patterns of single and paired responses differed beyond the expected variations in amplitude. MATERIALS AND METHODS: LICI was delivered as single and paired pulses to the motor cortex (MC) and dorsolateral prefrontal cortex (DLPFC) in 33 healthy subjects with TMS-EEG. RESULTS: Significant differences (p<0.0001) between the unconditioned and conditioned evoked activity were found for both the DLPFC and MC using both methods (i.e., DFT and HT) after correcting for multiple comparisons in the time-frequency domain. The influence of inhibition was found to be significantly larger in space and time than previously considered. Single and paired conditions differ in intensity, but also in their topographic pattern (i.e., the specific spatiotemporal configuration of active sources). CONCLUSION: Similar results were found by both DFT and HT. The effect of inhibition across the cortex was also found to be complex and extended. In particular, it was found that LICI may be measured with high sensitivity in areas that were relatively distant from the stimulation site, which may have important practical applications. The analysis presented in this study overcomes some limitations of previous studies and could serve as a key reference for future studies examining TMS-indices of inhibition/excitation in healthy and diseased states.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".